Snoring classified: The Munich-Passau Snore Sound Corpus

Christoph Janott,Maximilian Schmitt, Yue Zhang,Kun Qian, Vedhas Pandit,Zixing Zhang,Clemens Heiser,Winfried Hohenhorst, Michael Herzog,Werner Hemmert,Björn Schuller

Computers in Biology and Medicine（2018）

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摘要

•Snore sound excitation locations can be distinguished by acoustic properties.•Automatic classification models based on speech-features prove successful.•The ComParE feature set, used successfully in paralinguistics, showed best results.•Mel Frequency Cepstral Coefficients (MFCCs) were the best-performing single subset.•Formant-based features alone yielded inferior results.

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关键词

Obstructive Sleep Apnea,Primary snoring,Snore sound classification,Machine learning,Drug-Induced Sleep Endoscopy

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